NDLI: Long Horizon End-to-End Delay Forecasts: A Multi-Step-Ahead Hybrid Approach

Content Provider	IEEE Xplore Digital Library
Author	Vinh Bui Weiping Zhu Pescape, A. Botta, A.
Copyright Year	2007
Description	Author affiliation: Univ. of New South Wales, Sydney (Vinh Bui; Weiping Zhu)
Abstract	A long horizon end-to-end delay forecast, if possible, will be a breakthrough in traffic engineering. This paper introduces a hybrid approach to forecast end-to-end delays using wavelet transforms in combination with neural network and pattern recognition techniques. The discrete wavelet transform is implemented to decompose delay time series into a set of wavelet components, which is comprised of an approximate component and a number of detail components. Thus, it turns the problem of long horizon delay forecasting into a set of shorter horizon wavelet coefficient forecasting problems. A recurrent multi-layered perceptron neural network is applied to forecast coefficients of the wavelet approximate component, which represents the trend of the delay series. The k-nearest neighbors technique is used to forecast coefficients of the wavelet detail components, which reflect the burstiness of background traffic. The proposed approach has been verified in both simulation and over real heterogeneous networks showing promising results in terms of averaged normalized root mean square error. In addition, when compared to some existing and well known approaches it presents the superior performance.
Starting Page	825
Ending Page	832
File Size	2442482
Page Count	8
File Format	PDF
ISBN	9781424415205
ISSN	15301346
DOI	10.1109/ISCC.2007.4381513
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-07-01
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Propagation delay Discrete wavelet transforms Telecommunication traffic Neural networks Pattern recognition Delay effects Wavelet coefficients Multilayer perceptrons Multi-layer neural network Recurrent neural networks
Content Type	Text
Resource Type	Article
Subject	Signal Processing Mathematics Computer Networks and Communications Computer Science Applications Software

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